SciELO - Scientific Electronic Library Online

 
vol.14 número4Aprendiendo con meta-clasificadores a partir de flujos de datos no estacionariosUn enfoque ER/SBVR para la modelación conceptual en bases de datos de restricciones de integridad índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

  • Não possue artigos citadosCitado por SciELO

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Revista Cubana de Ciencias Informáticas

versão On-line ISSN 2227-1899

Resumo

COTO PALACIO, Jessica; JIMENEZ MARTINEZ, Yailen  e  NOWE, Ann. Application of neuro-fuzzy systems in the classification of reports in scheduling problems. Rev cuba cienc informat [online]. 2020, vol.14, n.4, pp.34-47.  Epub 01-Dez-2020. ISSN 2227-1899.

Scheduling is a very broad area in which many researchers have focused in the past years. In most of the companies this process is usually done manually or semi automatically. In this work we propose the application of neuro-fuzzy systems in the classification of reports in scheduling problems, a necessary step to identify in which resource the report will be processed, in order to build the work sequence or schedule for the day. For the classification of the reports arriving to the system four neuro-fuzzy algorithms are used. The experiments show that the algorithm that obtains the best results is IVTURS, and the fuzzy rules obtained are analyzed to arrive to conclusions regarding the distributions of reports among the resources.

Palavras-chave : report classification; scheduling problems; neuro-fuzzy systems.

        · resumo em Espanhol     · texto em Espanhol     · Espanhol ( pdf )